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Thesportsdb

by io.github.pipeworx-io

Remember

remember
Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context: data is scoped by identifier, persistent for authenticated users, and 24-hour retention for anonymous sessions. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the primary purpose. No fluff; every sentence adds critical information. Highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description could mention the return value (e.g., success indication). However, it adequately covers persistence, scope, and pairing with other tools. It might also clarify behavior on overwrite, but idempotentHint suggests idempotent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both key and value. The description adds semantic value by providing example key patterns (e.g., 'subject_property', 'target_ticker') and value types (findings, addresses, preferences, notes), enhancing understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses clear verbs ('Save data the agent will need to reuse later') and specifies the resource (key-value pair). It distinguishes from sibling tools recall and forget by mentioning them, making the tool's purpose distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool: 'Use when you discover something worth carrying forward' and provides concrete examples (resolved ticker, target address, etc.). It also mentions pairing with recall and forget, guiding the agent on alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Thesportsdb toolsInspect
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TDQS

B3.3/5.0
Disambiguation2/5

The sports tools are distinct, but the majority of the set has heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve as query/entry-point tools, with ask_pipeworx and ask_pipeworx_beta explicitly identical. The Polymarket family (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) also blurs together.

Naming Consistency2/5

The sports subset follows a clean verb_noun pattern (get_player, list_leagues, search_teams), but the rest mixes several naming schemes: ask_pipeworx*, pipeworx_* prefixed tools, polymarket_* tools, one-word verbs (remember, recall, forget), and compound names like scan_competitor_ai_presence. No single consistent convention governs the set.

Tool Count2/5

42 tools is far too many for a server named Thesportsdb; only 10 tools relate to sports data, while 32 belong to an unrelated Pipeworx data/betting/memory platform. The set feels like two or three servers merged into one, making it heavy and unfocused for any single purpose.

Completeness2/5

For the stated sports domain, the surface is partial: you can get teams, players, league tables, and recent/next fixtures, but there are no player statistics, head-to-head records, venue details, or season history — leaving notable gaps. The Pipeworx half is broad but doesn't belong in a server with this name, so the set as a whole is incomplete for its apparent purpose.

Resources